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Expert Systems
F451 AS Computing
Expert Systems - Definition
Created from research into Artificial
Intelligence – AI
Also known as knowledge based systems.
Based on Facts & Rules.
A system that attempts to replicate a human
expert in solving specific problems or
making decisions
Expert System Components
Comprises of 3 things
Knowledge Base
Experts in the field are interviewed.
Information collected from many sources.
Information is entered into the knowledge
base.
Inference Engine
Algorithms that interrogate the knowledge
base.
HCI
Allows anyone to use system. Must be clear
and easy to use – often Natural Language
Expert System - features
Limited area of expertise
Rule based
Can operate with uncertain data
Delivers reasoned advice
Expert Systems – main components
outputs
inputs
Interface
Expert
System
rules
facts
Knowledge
base
computer program
Inference
engine
Expert systems - uses
Medical diagnosis
Fault diagnosis
Geological surveys
Social services
Industrial uses
Expert Systems – case studies and demos
ELSIE – 1990’s quantity surveying tool
http://www.exsys.com/demomain.html
For demos of the following expert systems, including:
Cessna Diagnostic & Repair Systems
Immigration and Naturalization Service
Environmental Compliance Self Appraisal
Weather Instrument Product Selector
State of Wisconsin - Public School Disciplinary Action Advisor
DriveRight Trip 500AL Hardware Installation Expert System
Expert Systems - benefits
Can be faster than human experts
Cost reduction over alternative diagnostics
High reliability possible
Consistent, rationalised decisions & results
Encapsulates and distributes expertise

Can be used as a repository of knowledge
Expert Systems - Limitations
Can make mistakes and will not learn from them
Expert knowledge is hard to obtain. Systems work
best when problem is clearly defined and rules are
clearly stated
Can create a dearth of skills
Stifles creative processes and exception handling
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